title: Models for forecasting hospital bed requirements in the acute sector.
abstract: OBJECTIVE
  The aim was to evaluate the current approach to forecasting hospital bed requirements.
  
  
  METHODS
  The study was a time series and regression analysis. The time series for mean duration of stay for general surgery in the age group 15-44 years (1969-1982) was used in the evaluation of different methods of forecasting future values of mean duration of stay and its subsequent use in the formation of hospital bed requirements.
  
  
  RESULTS
  It has been suggested that the simple trend fitting approach suffers from model specification error and imposes unjustified restrictions on the data. Time series approach (Box-Jenkins method) was shown to be a more appropriate way of modelling the data.
  
  
  CONCLUSIONS
  The simple trend fitting approach is inferior to the time series approach in modelling hospital bed requirements.
authors.affiliation: Department of Community Medicine, Charing Cross and Westminster Medical School, London.
authors.forename: R D
authors.initials: RD
authors.lastname: Farmer
authors.forename: J
authors.initials: J
authors.lastname: Emami
mesh_terms: D000293:Adolescent; D000328:Adult; D001509:Bed Occupancy / Q000639:trends*; D004630:Emergencies; D005544:Forecasting / Q000379:methods*; D006301:Health Services Needs and Demand / Q000706:statistics & numerical data; D006742:Hospital Bed Capacity; D006752:Hospital Planning / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data; D015233:Models, Statistical; D010343:Patient Admission / Q000706:statistics & numerical data; D012044:Regression Analysis